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At least 739 records · Page 41

SBOL Visual: A Graphical Language for Genetic Designs

Synthetic Biology Open Language (SBOL) Visual is a graphical standard for genetic engineering. We report that it consists of symbols representing DNA subsequences, including regulatory elements and DNA assembly features. These symbols can be used to draw illustrations for communication and instruction, and as image assets for computer-aided design. SBOL Visual is a community standard, freely available for personal, academic, and commercial use (Creative Commons CC0 license). We provide prototypical symbol images that have been used in scientific publications and software tools. We encourage users to use and modify them freely, and to join the SBOL Visual community: http://www.sbolstandard.org/visual.

59 BASIC BIOLOGICAL SCIENCES↗

Structural, electronic and optical properties of novel carbonate fluorides ABCO{sub 3}F (A=K, Rb, Cs; B=Ca, Sr)

In the present study, we performed first principles calculations on the electronic and optical properties of layered alkali–alkaline earth carbonate fluorides which attract attention in the domain of nonlinear optics. The calculated lattice parameters and volumes with and without inclusion of van der Waals (vdW) correction methods to standard density functional methods were compared with experiments. We observed that vdW interactions are predominant in RbCaCO{sub 3}F and CsCaCO{sub 3}F as compared with other computed compounds. The calculated bulk modulus from single crystal elastic constants reveals that these materials are all relatively harder than the KH{sub 2}PO{sub 4} (KDP) crystal. We also found that these materials are wide band gap insulators as obtained from Tran–Blaha modified Becke–Johnson potential. The linear optical properties such as dielectric function, refractive indices, birefringence and absorption spectra are presented. Finally, the calculated birefringence values indicate that these crystals could be promising for producing phase matching in the deep ultra-violet region. - Graphical abstract: The co- and anti-parallel alignment of CO{sub 3} groups leads to larger and smaller SHG coefficients in (a) KCaCO{sub 3}F, (b) KSrCO{sub 3}F, (c) RbSrCO{sub 3}F, (d) RbCaCO{sub 3}F, and (e) CsCaCO{sub 3}F. - Highlights: • Effect of van der Waals interactions on structural properties. • Single-crystalline elastic constants and mechanical stability. • Electronic properties. • Linear optical properties. • Comparison of present computed compounds with other well known materials in non-linear optical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulations of the shock-driven Kelvin–Helmholtz instability in inclined gas curtains

In this paper, we present simulation results for the two-dimensional, shock-driven Kelvin–Helmholtz instability. Simulations are performed with a Mach 2.0 shock propagating through a finite-thickness curtain of gas inclined at an angle α0=30° with respect to the shock plane. After the passage of the shock, the gas curtain is accelerated along its axis. A perturbation develops due to shock reflection near the lower wall, and a Kelvin–Helmholtz instability forms near the vertical center of the curtain. This is the first known numerical reproduction of these phenomena that have previously been observed in experiments with an inclined cylindrical gas column. The effects of varying Mach number and column width were explored in detail to complement experimental data. Additionally, the dependence of the Kelvin–Helmholtz wavelength on Mach number closely matches the relationship observed in experiments. This supports the notion that the observed instability is effectively two-dimensional and inviscid (like classical Kelvin–Helmholtz). The growth rate of the perturbations in the gas curtain was also found to be similar for different Mach numbers. The perturbation at the curtain foot, previously unreported in experiments, was found to have a similar relationship to Mach number as the Kelvin–Helmholtz instability. Both perturbation wavelengths are found to be proportional to layer width. Simulations were performed with the fast interfaces and transport in the atmosphere, an exascale ready, graphics processing unit-accelerated compressible flow solver developed at the University of New Mexico.

42 ENGINEERING↗

MO-FG-CAMPUS-TeP1-03: Pre-Treatment Surface Imaging Based Collision Detection

Purpose: Modern radiotherapy increasingly employs large immobilization devices, gantry attachments, and couch rotations for treatments. All of which raise the risk of collisions between the patient and the gantry / couch. Collision detection is often achieved by manually checking each couch position in the treatment room and sometimes results in extraneous imaging if collisions are detected after image based setup has begun. In the interest of improving efficiency and avoiding extra imaging, we explore the use of a surface imaging based collision detection model. Methods: Surfaces acquired from AlignRT (VisionRT, London, UK) were transferred in wavefront format to a custom Matlab (Mathworks, Natick, MA) software package (CCHECK). Computed tomography (CT) scans acquired at the same time were sent to CCHECK in DICOM format. In CCHECK, binary maps of the surfaces were created and overlaid on the CT images based on the fixed relationship of the AlignRT and CT coordinate systems. Isocenters were added through a graphical user interface (GUI). CCHECK then compares the inputted surfaces to a model of the linear accelerator (linac) to check for collisions at defined gantry and couch positions. Note, CCHECK may be used with or without a CT. Results: The nominal surface image field of view is 650 mm × 900 mm, with variance based on patient position and size. The accuracy of collision detections is primarily based on the linac model and the surface mapping process. The current linac model and mapping process yield detection accuracies on the order of 5 mm, assuming no change in patient posture between surface acquisition and treatment. Conclusions: CCHECK provides a non-ionizing method to check for collisions without the patient in the treatment room. Collision detection accuracy may be improved with more robust linac modeling. Additional gantry attachments (e.g. conical collimators) can be easily added to the model.

60 APPLIED LIFE SCIENCES↗

Vectorization, threading, and cache-blocking considerations for hydrocodes on emerging architectures

This work reports on considerations for improving computational performance in preparation for current and expected changes to computer architecture. The algorithms studied will include increasingly complex prototypes for radiation hydrodynamics codes, such as gradient routines and diffusion matrix assembly (e.g., in [1-6]). The meshes considered for the algorithms are structured or unstructured meshes. The considerations applied for performance improvements are meant to be general in terms of architecture (not specifically graphical processing unit (GPUs) or multi-core machines, for example) and include techniques for vectorization, threading, tiling, and cache blocking. Out of a survey of optimization techniques on applications such as diffusion and hydrodynamics, we make general recommendations with a view toward making these techniques conceptually accessible to the applications code developer. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

97 MATHEMATICS AND COMPUTING↗

Simulating Catalysis with Realistic Pellet Geometries Using Mesoflow: A Case Study of Catalytic Propane Dehydrogenation

We present a case study of catalytic propane dehydrogenation with our open-source multiphysics solver, Mesoflow. The solver was developed to simulate reactive flow coupled to heterogeneous catalytic reactions and deactivation in the context of complex, mesoscale geometry. The method leverages cartesian block-structured adaptive mesh refinement to capture realistic catalyst microstructural features acquired directly from X-ray computed tomography data. A kinetic model for propane dehydrogenation and catalyst deactivation was developed based on temporal analysis of products (TAP) reactor experiments. The TAP reactor experiments allow for precise characterization of intrinsic kinetic reaction steps which are implemented into Mesoflow simulations to model the spatial and temporal evolution of reactants, products, and catalyst active sites. The short-term and long-term deactivation behavior is studied by using XCT data collected from fresh and aged catalyst pellets, which exhibit different microstructural features. This study employs time-splitting algorithms to connect disparate reaction and flow timescales, enabling the simulations to achieve realistic deactivation timescales on the order of minutes while the flow time-scales for small particles (100 microns) are several milliseconds. We also introduce a flexible automated python script that writes the necessary files to construct a Mesoflow simulation from user-created chemical mechanisms. We will also introduce a few new features that are added to Mesoflow such as higher order schemes, implicit chemistry integrators and the ability to run on AMD and NVIDIA graphics-processing-units.

AMReX↗

Fast automated analysis of strong gravitational lenses with convolutional neural networks

Quantifying image distortions caused by strong gravitational lensing—the formation of multiple images of distant sources due to the deflection of their light by the gravity of intervening structures—and estimating the corresponding matter distribution of these structures (the ‘gravitational lens’) has primarily been performed using maximum likelihood modelling of observations. Our procedure is typically time- and resource-consuming, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers. Accurate analysis of a single gravitational lens can take up to a few weeks and requires expert knowledge of the physical processes and methods involved. Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys. We report the use of deep convolutional neural networks to estimate lensing parameters in an extremely fast and automated way, circumventing the difficulties that are faced by maximum likelihood methods. We also show that the removal of lens light can be made fast and automated using independent component analysis of multi-filter imaging data. Our networks can recover the parameters of the ‘singular isothermal ellipsoid’ density profile, which is commonly used to model strong lensing systems, with an accuracy comparable to the uncertainties of sophisticated models but about ten million times faster: 100 systems in approximately one second on a single graphics processing unit. These networks can provide a way for non-experts to obtain estimates of lensing parameters for large samples of data.

79 ASTRONOMY AND ASTROPHYSICS↗

SCALE Code System 6.2.2

The SCALE Code System is a widely used modeling and simulation suite for nuclear safety analysis and design that is developed, maintained, tested, and managed by the Reactor and Nuclear Systems Division (RNSD) of Oak Ridge National Laboratory (ORNL). SCALE provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor physics, radiation shielding, radioactive source term characterization, and sensitivity and uncertainty analysis. Since 1980, regulators, licensees, and research institutions around the world have used SCALE for safety analysis and design. SCALE provides an integrated framework with dozens of computational modules including 3 deterministic and 3 Monte Carlo radiation transport solvers that are selected based on the desired solution strategy. SCALE includes current nuclear data libraries and problem-dependent processing tools for continuous-energy (CE) and multigroup (MG) neutronics and coupled neutron-gamma calculations, as well as activation, depletion, and decay calculations. SCALE includes unique capabilities for automated variance reduction for shielding calculations, as well as sensitivity and uncertainty analysis. SCALE’s graphical user interfaces assist with accurate system modeling, visualization of nuclear data, and convenient access to desired results. SCALE 6.2 represents one of the most comprehensive revisions in the history of SCALE, providing several new capabilities and significant improvements in many existing features.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

The General Atomic and Molecular Electronic Structure System (GAMESS): Novel Methods on Novel Architectures

The primary focus of GAMESS over the last 5 years has been the development of new high-performance codes that are able to take effective and efficient advantage of the most advanced computer architectures, both CPU and accelerators. These efforts include employing density fitting and fragmentation methods to reduce the high scaling of well-correlated (e.g., coupled-cluster) methods as well as developing novel codes that can take optimal advantage of graphical processing units and other modern accelerators. Because accurate wave functions can be very complex, an important new functionality in GAMESS is the quasi-atomic orbital analysis, an unbiased approach to the understanding of covalent bonds embedded in the wave function. Finally, best practices for the maintenance and distribution of GAMESS are also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring 2D X-ray diffraction phase fraction analysis with convolutional neural networks: Insights from kinematic-diffraction simulations

Abstract Deep-learning models are effective for analyzing the complex information in 2D X-ray diffraction (XRD) patterns. Accurately collecting parameters of the material sample is crucial during model training, significantly impacting model performance. In this study, we employ a kinematic-diffraction simulator to generate simulated 2D XRD patterns for Ti–6Al–4V alloy, allowing precise control of sample parameters. These simulated patterns are used to train convolutional neural networks, predicting $$\upbeta$$ β -phase volume fractions. The training data set consists exclusively of 2D XRD patterns with pure $$\upalpha$$ α - or pure $$\upbeta$$ β -phase, while the testing set incorporates patterns with intermediate phase volume fraction. In particular, we investigate how the architectures of the model influence prediction reliability and computational performance. Experimental results reveal that, with appropriate training, the convolutional neural network accurately detects intermediate phase volume fractions even trained with only pure-phase patterns, achieving a mean square error accuracy of $$9.4 \times 10^{-4}$$ 9.4 × 10 - 4 . Graphical abstract

Yue, Weiqi↗

Using EMIS to Identify Top Opportunities for Commercial Building Efficiency

Energy Management and Information Systems (EMIS) comprise a broad family of tools and services to manage commercial building energy use. These technologies offer a mix of capabilities to store, display, and analyze energy use and system data, and in some cases, provide control. EMIS technologies enable 10–20 percent site energy savings in best practice implementations. Energy Information System (EIS) and Fault Detection and Diagnosis (FDD) systems are two key technologies in the EMIS family. Energy Information Systems are broadly defined as the web-based software, data acquisition hardware, and communication systems used to analyze and display building energy performance. At a minimum, an EIS provides daily, hourly or sub-hourly interval meter data at the whole-building level, with graphical and analytical capability. Fault Detection and Diagnosis systems automatically identify heating, ventilation, and air-conditioning (HVAC) system or equipment-level performances issues, and in some cases are able to isolate the root causes of the problem. They use computer algorithms to continuously analyze system-level operational data to detect faults and diagnose their causes. Many FDD tools integrate the trend log data from a Building Automation System (BAS) but otherwise are stand-alone software packages; other types of FDD tools are implemented as “on-board” equipment-embedded diagnostics. (This document focuses on the former.) Analysis approaches adopted in FDD technologies span a variety of techniques from rule-based methods to process history-based approaches. FDD tools automate investigations that can be conducted via manual data inspection by someone with expert knowledge, thereby expanding accessibility and breath of analysis opportunity, and also reducing complexity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Visualization for Hyper-Heuristics: Back-End Processing

Modern society is faced with increasingly complex problems, many of which can be formulated as generate-and-test optimization problems. Yet, general-purpose optimization algorithms may sometimes require too much computational time. In these instances, hyperheuristics may be used. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario, finding the solution significantly faster than its predecessor. However, it may be difficult to understand exactly how a design was derived and why it should be trusted. This project aims to address these issues by creating an easy-to-use graphical user interface (GUI) for hyper-heuristics and an easy-to-understand scientific visualization for the produced solutions. To support the development of this GUI, my portion of the research involved developing algorithms that would allow for parsing of the data produced by the hyper-heuristics. This data would then be sent to the front-end, where it would be displayed to the end user.

97 MATHEMATICS AND COMPUTING↗

GPU acceleration of hybrid functional calculations in the SPARC electronic structure code

We present a Graphics Processing Unit (GPU)-accelerated version of the real-space SPARC electronic structure code for performing hybrid functional calculations in generalized Kohn–Sham density functional theory. In particular, we develop a batch variant of the recently formulated Kronecker product-based linear solver for the simultaneous solution of multiple linear systems. We then develop a modular, math kernel based implementation for hybrid functionals on NVIDIA architectures, where computationally intensive operations are offloaded to the GPUs, while the remaining workload is handled by the central processing units (CPUs). Considering bulk and slab examples, we demonstrate that GPUs enable up to 8× speedup in node-hours and 80× in core-hours compared to CPU-only execution, reducing the time to solution on V100 GPUs to around 300 s for a metallic system with over 6000 electrons, and significantly reducing the computational resources required for a given wall time.

Kohn-Sham density functional theory↗

High-speed GPU-based finite element simulations for NDT

The finite element method solved with explicit time increments is a general approach which can be applied to many ultrasound problems. It is widely used as a powerful tool within NDE for developing and testing inspection techniques, and can also be used in inversion processes. However, the solution technique is computationally intensive, requiring many calculations to be performed for each simulation, so traditionally speed has been an issue. For maximum speed, an implementation of the method, called Pogo [Huthwaite, J. Comp. Phys. 2014, doi: 10.1016/j.jcp.2013.10.017], has been developed to run on graphics cards, exploiting the highly parallelisable nature of the algorithm. Pogo typically demonstrates speed improvements of 60-90x over commercial CPU alternatives. Pogo is applied to three NDE examples, where the speed improvements are important: guided wave tomography, where a full 3D simulation must be run for each source transducer and every different defect size; scattering from rough cracks, where many simulations need to be run to build up a statistical model of the behaviour; and ultrasound propagation within coarse-grained materials where the mesh must be highly refined and many different cases run.

36 MATERIALS SCIENCE↗

Cluster perturbation theory X: A parallel implementation of Lagrangian perturbation series for the coupled cluster singles and doubles ground-state energy through fifth order

We describe an efficient implementation of cluster perturbation and Møller-Plesset Lagrangian energy series through fifth order that target the coupled cluster singles and doubles energy utilizing the resolution of the identity approximation. We illustrate the computational performance of the implementation by performing ground state energy calculations on systems with up to 1200 basis functions using a single node and by comparison to conventional CCSD calculations. We further show that our hybrid MPI/OMP parallel implementation that also utilizes graphical processing units can be used to obtain fifth order energies on systems with almost 1200 basis functions with a 90 minute "time to solution" running on Frontier at Oak Ridge National Laboratory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Zodiac: A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data

Background: Genetic interactions play a critical role in cancer development. Existing knowledge about cancer genetic interactions is incomplete, especially lacking evidences derived from large-scale cancer genomics data. The Cancer Genome Atlas (TCGA) produces multimodal measurements across genomics and features of thousands of tumors, which provide an unprecedented opportunity to investigate the interplays of genes in cancer. Methods: We introduce Zodiac, a computational tool and resource to integrate existing knowledge about cancer genetic interactions with new information contained in TCGA data. It is an evolution of existing knowledge by treating it as a prior graph, integrating it with a likelihood model derived by Bayesian graphical model based on TCGA data, and producing a posterior graph as updated and data-enhanced knowledge. In short, Zodiac realizes “Prior interaction map + TCGA data → Posterior interaction map.” Results: Zodiac provides molecular interactions for about 200 million pairs of genes. All the results are generated from a big-data analysis and organized into a comprehensive database allowing customized search. In addition, Zodiac provides data processing and analysis tools that allow users to customize the prior networks and update the genetic pathways of their interest. Zodiac is publicly available at www.compgenome.org/ZODIAC. Conclusions: Zodiac recapitulates and extends existing knowledge of molecular interactions in cancer. It can be used to explore novel gene-gene interactions, transcriptional regulation, and other types of molecular interplays in cancer.

Zhu, Yitan↗

Rapid evaluation and quality control of next generation sequencing data with FaQCs

Background: Next generation sequencing (NGS) technologies that parallelize the sequencing process and produce thousands to millions, or even hundreds of millions of sequences in a single sequencing run, have revolutionized genomic and genetic research. Because of the vagaries of any platform's sequencing chemistry, the experimental processing, machine failure, and so on, the quality of sequencing reads is never perfect, and often declines as the read is extended. These errors invariably affect downstream analysis/application and should therefore be identified early on to mitigate any unforeseen effects. Results: Here we present a novel FastQ Quality Control Software (FaQCs) that can rapidly process large volumes of data, and which improves upon previous solutions to monitor the quality and remove poor quality data from sequencing runs. Both the speed of processing and the memory footprint of storing all required information have been optimized via algorithmic and parallel processing solutions. The trimmed output compared side-by-side with the original data is part of the automated PDF output. We show how this tool can help data analysis by providing a few examples, including an increased percentage of reads recruited to references, improved single nucleotide polymorphism identification as well as de novo sequence assembly metrics. Conclusion: FaQCs combines several features of currently available applications into a single, user-friendly process, and includes additional unique capabilities such as filtering the PhiX control sequences, conversion of FASTQ formats, and multi-threading. The original data and trimmed summaries are reported within a variety of graphics and reports, providing a simple way to do data quality control and assurance.

59 BASIC BIOLOGICAL SCIENCES↗

Prototype Distributed Ledger Technology of UF 6 Cylinder Tracking in Ethereum

We have created a demonstration permissioned Distributed Ledger Technology (DLT) datastore for the UF 6 cylinder tracking safeguards use-case utilizing the Ethereum DLT framework and using Solidity for smart contract code. Our demonstration creates a simulated dataset representing tracking of 75,000 UF 6 cylinders across 11 example nuclear facilities worldwide. Our DLT system allows for easy input and reading of shipping and receiving data, including a Graphical User Interface (GUI). Sandia’s Emulytics capability was leveraged to help create the DLT node network and assess performance. We find that our DLT prototype can easily handle to ~150,000 UF 6 cylinder shipments per year worldwide, without any excessive computational or storage burden on the IAEA or Member States. Next steps could include a demonstration to the IAEA and potentially demonstrating integration with TradeLens, a DLT in use by a consortium of international shipping companies representing over half of world shipping trade.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗